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Databricks. Data, analytics and AI on one platform

Deliver real-time analytics, scaled out data warehouse, and AI/ML enhanced applications using MongoDB and Databricks.

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The Databricks Lakehouse Platform

The Databricks Lakehouse Platform combines the best elements of data lakes and data warehouses to deliver the reliability, strong governance, and performance of data warehouses, with the openness, flexibility, and machine learning support of data lakes.

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Connect your Lakehouse to MongoDB Using a Databricks Notebook

Databricks now features MongoDB as a data source. Create a unified, real-time processing layer by integrating Databricks Lakehouse with MongoDB Atlas.

MongoDB Spark Connector and Databricks

Make operationalizing ML-enhanced applications easy by leveraging Databricks’ real-time data ingestion and processing capabilities for all types of data. Then activate analytics in MongoDB by serving results to user-based applications.

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Import/Export Data via Object Store

With the MongoDB aggregation pipeline and $out, you can pre-process and transform data before exporting it in an analytics-optimized columnar format to object stores (such as Amazon S3) for seamless ingest into Databricks. This allows you to process bi-directionally targeted (and large) datasets.

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How to Integrate Databricks and MongoDB

Linking your MongoDB Atlas database to data stored in the Databricks Lakehouse has never been easier. Learn more about the Databricks MongoDB Notebook.
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